One of the first things to consider before implementation even begins: Map a clear and accurate picture of your business processes, defining who does what, how handoffs occur, and who needs to be notified when. These will guide discussions with the vendor and IT and help you decide whether to implement your current workflow or improve it first. For example, we replaced our separate web form conflict of interest and principal investigator certification forms with one integrated submission form in the EGMS.
During vendor-led training, ask more questions than you think you need to. Do not assume terms like “automatic notifications” or “routing” matches your expectations. We heard/interpreted/assumed that alerts would trigger as the EGMS form fields were completed; however, the alerts do not trigger until after a principal investigator routes the form. Using the sandbox heavily — this is how you validate that the system works the way you need it to. Testing can be key here: Test processes and workflow by inputting sample grants into the system before moving forward with real data.
Financial structure is also important. Universities often have hundreds of department or organization codes, many of which are irrelevant to grants. Decide which codes matter and how they map into the new system. Be clear which are the “systems of record.” Some information may appropriately live in the EGMS, while financial data will almost always remain in the accounting system. Senior leadership can guide these decisions.
And do not overlook IT — well before the contract is signed. They are more than technical support; they are interpreters (not everyone speaks “IT”), project managers, integration specialists, and know timelines for IT resource availability. EGMS systems are not plug-and-play. Don’t get the contract and then reach out to IT for help.
Approval chains need careful attention. Universities must ensure chair and dean approval before a proposal leaves campus to document resource commitments. Document your approval pathways and notifications, which translate into workflows and triggers. Decide how proposal drafts will be handled — for example, we still manage drafts outside the system and upload only final versions.
Finally, double your estimate for migrating legacy data. It is far more time-consuming than expected and requires extensive spreadsheets, validation, and cleanup. I believe it was worth it, but there's a reason it’s called growing pains. Then plan how you will manage quality during the first months of go-live.
The whole journey was an adventure. We learned a lot and grew closer as a group. I now know our processes better than ever! We are leaps and bounds past where we were with disparate systems. One thing that did not go well was our multiple attempts to import the legacy data — we thought we asked the right questions. Getting the “sandbox” version fixed and moving it to production also took a ton of work. Beware of the hyphens! They bite!
Despite the effort, the payoff of implementing an EGMS is great: transparency, real-time access, and reporting that truly empowers faculty and strengthens accountability across the research enterprise. I’m grateful our university invested in supporting this amazing tool!